Plaid and Backbase Team on Faster Bank Customer Onboarding

Artificial intelligence (AI)-powered banking platform Backbase has launched a partnership with financial services data analytics network Plaid.

The collaboration, announced Monday (Feb. 16), is designed to tackle what the companies say is one of the biggest challenges in banking: data fragmentation that impedes innovation and limits the customer experience.

“Financial institutions face a common problem: Data lives in silos, legacy integrations break constantly, customer onboarding often takes several days—and lack of visibility across databases means creating personalized experiences is challenging and costly,” the companies said in a news release provided to PYMNTS.

The partnership aims to address this issue by melding Plaid’s financial data connectivity with Backbase’s platform. This lets banks more quickly onboard customers faster, aggregate account data and offer personalized financial journeys.

The solution is available now to banks worldwide via Backbase’s website.

“Artificial intelligence is rapidly changing what’s possible in financial services, but only with strong data foundations,” said Adam Yoxtheimer, head of partnerships at Plaid. “By combining Plaid’s real-time connectivity and intelligence with Backbase’s banking platform, more banks can access the permissioned data and corresponding insights needed to deliver enhanced, personalized experiences.”

PYMNTS took a closer look at the use of AI in the finance world last week, noting that the most  consequential AI deployments in the sector are ones customers can’t see.

“They are unfolding inside compliance queues, cash management dashboards and payment routing engines, where AI agents now initiate tasks and move money based on live signals,” that report said. “That transition marks the first real test of whether financial institutions trust AI with operational authority.”

Agentic AI, PYMNTS added, has gone from experimental pilots and to the operational core of financial institutions. Unlike earlier generative AI tools that responded to prompts, agentic systems can plan, reason and carry out multistep workflows with limited human intervention.

The shift is resonating inside finance departments. PYMNTS Intelligence research shows that 43% of chief financial officers expect agentic AI to have a strong impact on dynamic budget reallocation based on real-time cost signals, with another 47% forecasting a moderate impact.

“Finance leaders are increasingly relying on AI agents to monitor spending, optimize cash flow timing and surface anomalies without waiting for month-end closes,” PYMNTS wrote.